Benefits of SEI-CMU Collaboration regarding Use of Causal Learning

Abstract

Contents include: Context of SCOPE Research; Initial SCOPE Causal Search Results; Benefits of CMU Collaboration; Lessons Learned from CMU Collaboration; Moderate Future: Causal Learning for Simulation and Test ; Moderate Future: Causal Learning for Sustainment ; Long Term Future: (Causal Learning Examples).

Document Details

• Document Type: Technical Report
• Publication Date: Jan 01, 2018
• Accession Number: AD1084337

Entities

People

• Dave Danks
• Robert W. Stoddard

Organizations

• Carnegie Mellon University

Tags

Communities of Interest

• Autonomy

DTIC Thesaurus Topics

• Autonomous Systems
• Causal Reasoning
• Cognitive Systems Engineering
• Complex Systems
• Cost Estimates
• Costs
• Cyber Defense Techniques
• Digital Engineering
• Engineering
• Learning
• Lessons Learned
• Machine Learning
• Psychology
• Software Development
• Teamwork
• Technical Debt
• Universities

Readers

• Neural Network Machine Learning.
• Software Engineering.